A timely presentation of new results, challenges, and opportunities in the quickly developing field of nuclear cluster physics, presented by an international group of eminent theoretical and experimental scientists active in the field. Their work reveals how correlations of nucleons can appear spontaneously, propagate, and survive in nuclear matter at both low and high densities. Characteristic nuclear substructures, beyond those predicted by mean-field or collective scenarios, appear on microscopic and cosmic length scales. They can influence the dynamics of fusion of light nuclei and the decay of heavy, fissioning nuclei or of systems produced transiently in heavy-ion reactions. A must-read for young scientists entering the field and a valuable resource for more seasoned nuclear researchers!
This book provides an introduction to data science and offers a practical overview of the concepts and techniques that readers need to get the most out of their large-scale data mining projects and research studies. It discusses data-analytical thinking, which is essential to extract useful knowledge and obtain commercial value from the data. Also known as data-driven science, soft computing and data mining disciplines cover a broad interdisciplinary range of scientific methods and processes. The book provides readers with sufficient knowledge to tackle a wide range of issues in complex systems, bringing together the scopes that integrate soft computing and data mining in various combinations of applications and practices, since to thrive in these data-driven ecosystems, researchers, data analysts and practitioners must understand the design choice and options of these approaches. This book helps readers to solve complex benchmark problems and to better appreciate the concepts, tools and techniques used.
This book presents high-quality peer-reviewed papers from the International Conference on Advanced Communication and Computational Technology (ICACCT) 2019 held at the National Institute of Technology, Kurukshetra, India. The contents are broadly divided into four parts: (i) Advanced Computing, (ii) Communication and Networking, (iii) VLSI and Embedded Systems, and (iv) Optimization Techniques.The major focus is on emerging computing technologies and their applications in the domain of communication and networking. The book will prove useful for engineers and researchers working on physical, data link and transport layers of communication protocols. Also, this will be useful for industry professionals interested in manufacturing of communication devices, modems, routers etc. with enhanced computational and data handling capacities.
Atom probe microscopy enables the characterization of materials structure and chemistry in three dimensions with near-atomic resolution. This uniquely powerful technique has been subject to major instrumental advances over the last decade with the development of wide-field-of-view detectors and pulsed-laser-assisted evaporation that have significantly enhanced the instrument’s capabilities. The field is flourishing, and atom probe microscopy is being embraced as a mainstream characterization technique. This book covers all facets of atom probe microscopy—including field ion microscopy, field desorption microscopy and a strong emphasis on atom probe tomography. Atom Probe Microscopy is aimed at researchers of all experience levels. It will provide the beginner with the theoretical background and practical information necessary to investigate how materials work using atom probe microscopy techniques. This includes detailed explanations of the fundamentals and the instrumentation, contemporary specimen preparation techniques, experimental details, and an overview of the results that can be obtained. The book emphasizes processes for assessing data quality, and the proper implementation of advanced data mining algorithms. Those more experienced in the technique will benefit from the book as a single comprehensive source of indispensable reference information, tables and techniques. Both beginner and expert will value the way that Atom Probe Microscopy is set out in the context of materials science and engineering, and includes references to key recent research outcomes.
Here is a brilliant book that covers the major aspects of nanomaterials production. It integrates the many and varied chemical, material and thermo-dynamical facets of production, offering readers a new and unique approach to the subject. The mechanical, optical, and magnetic characteristics of nanomaterials are also presented in detail. Nanomaterials are a fast developing field of research and this book serves as both a reference work for researchers and a textbook for graduate students.
Distributed and Cloud Computing: From Parallel Processing to the Internet of Things offers complete coverage of modern distributed computing technology including clusters, the grid, service-oriented architecture, massively parallel processors, peer-to-peer networking, and cloud computing. It is the first modern, up-to-date distributed systems textbook; it explains how to create high-performance, scalable, reliable systems, exposing the design principles, architecture, and innovative applications of parallel, distributed, and cloud computing systems. Topics covered by this book include: facilitating management, debugging, migration, and disaster recovery through virtualization; clustered systems for research or ecommerce applications; designing systems as web services; and social networking systems using peer-to-peer computing. The principles of cloud computing are discussed using examples from open-source and commercial applications, along with case studies from the leading distributed computing vendors such as Amazon, Microsoft, and Google. Each chapter includes exercises and further reading, with lecture slides and more available online. This book will be ideal for students taking a distributed systems or distributed computing class, as well as for professional system designers and engineers looking for a reference to the latest distributed technologies including cloud, P2P and grid computing. - Complete coverage of modern distributed computing technology including clusters, the grid, service-oriented architecture, massively parallel processors, peer-to-peer networking, and cloud computing - Includes case studies from the leading distributed computing vendors: Amazon, Microsoft, Google, and more - Explains how to use virtualization to facilitate management, debugging, migration, and disaster recovery - Designed for undergraduate or graduate students taking a distributed systems course—each chapter includes exercises and further reading, with lecture slides and more available online
This book constitutes the refereed proceedings of the Second International Conference on Data Mining and Big Data, DMBD 2017, held in Fukuoka, Japan, in July/August 2017. The 53 papers presented in this volume were carefully reviewed and selected from 96 submissions. They were organized in topical sections named: association analysis; clustering; prediction; classification; schedule and sequence analysis; big data; data analysis; data mining; text mining; deep learning; high performance computing; knowledge base and its framework; and fuzzy control.
Learn Data Mining by doing data mining Data mining can be revolutionary-but only when it's done right. The powerful black box data mining software now available can produce disastrously misleading results unless applied by a skilled and knowledgeable analyst. Discovering Knowledge in Data: An Introduction to Data Mining provides both the practical experience and the theoretical insight needed to reveal valuable information hidden in large data sets. Employing a "white box" methodology and with real-world case studies, this step-by-step guide walks readers through the various algorithms and statistical structures that underlie the software and presents examples of their operation on actual large data sets. Principal topics include: * Data preprocessing and classification * Exploratory analysis * Decision trees * Neural and Kohonen networks * Hierarchical and k-means clustering * Association rules * Model evaluation techniques Complete with scores of screenshots and diagrams to encourage graphical learning, Discovering Knowledge in Data: An Introduction to Data Mining gives students in Business, Computer Science, and Statistics as well as professionals in the field the power to turn any data warehouse into actionable knowledge. An Instructor's Manual presenting detailed solutions to all the problems in the book is available online.
